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Study Of Trend Following System In Securities Investment Management

Posted on:2017-04-15Degree:MasterType:Thesis
Country:ChinaCandidate:Z P PanFull Text:PDF
GTID:2309330482498870Subject:Business management
Abstract/Summary:PDF Full Text Request
The Chinese stock market has gone through many bull and bear market conversions since the establishment of China Stock Exchange. However, only a small percentage of investors can get a stable profit, because they do not insist on a set of simple and practical investment methods. To get a steady profit, investors should adopt many effective investment approaches, such as the value investment theory, technical analysis theory, modern investment theory, and trend-following theory.This thesis chooses trend-following theory as the object of study. Build a trading system to achieve the trend following strategies of moving average, Donchian channel, as well as regularly exiting Donchian channel and Bollinger channel. Use these trading strategies respectively on the Shanghai Composite Index, Shenzhen Component Index, the GEM index and small board index to simulate trading. Trading results and indicators obtained show that moving averages and Bollinger are preferable strategies in China’s securities market, but Donchian channel strategy and regularly exiting Donchian channel strategy are not very effective. Based on the test results, a trend-following trading system with optimized parameters has been established. With historical segment data testing the trading system, the validity of it has been proved.The ideal result achieved by using the trend-following trading system in the ETF tests proves that it is advisable to apply the system to the actual trading market. This study is an exploration of the trend following and trading systems, intending to provide a reference for the investment decisions of investors and to offer a new idea for the quantitative trading and program trading in China.
Keywords/Search Tags:Trend Following, Trading system, Program Trading, Moving average
PDF Full Text Request
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